Insights into Nitrate-Reducing Fe(II) Oxidation Mechanisms through Analysis of Cell-Mineral Associations, Cell Encrustation, and Mineralogy in the Chemolithoautotrophic Enrichment Culture KS.

Most described nitrate-reducing Fe(II)-oxidizing bacteria (NRFeOB) are mixotrophic and depend on organic cosubstrates for growth. Encrustation of cells in Fe(III) minerals has been observed for mixotrophic NRFeOB but not for autotrophic phototrophic and microaerophilic Fe(II) oxidizers. So far, little is known about cell-mineral associations in the few existing autotrophic NRFeOB. Here, we investigate whether the designated autotrophic Fe(II)-oxidizing strain (closely related to Gallionella and Sideroxydans) or the heterotrophic nitrate reducers that are present in the autotrophic nitrate-reducing Fe(II)-oxidizing enrichment culture KS form mineral crusts during Fe(II) oxidation under autotrophic and mixotrophic conditions. In the mixed culture, we found no significant encrustation of any of the cells both during autotrophic oxidation of 8 to 10 mM Fe(II) coupled to nitrate reduction and during cultivation under mixotrophic conditions with 8 to 10 mM Fe(II), 5 mM acetate, and 4 mM nitrate, where higher numbers of heterotrophic nitrate reducers were present. Two pure cultures of heterotrophic nitrate reducers (Nocardioides and Rhodanobacter) isolated from culture KS were analyzed under mixotrophic growth conditions. We found green rust formation, no cell encrustation, and only a few mineral particles on some cell surfaces with 5 mM Fe(II) and some encrustation with 10 mM Fe(II). Our findings suggest that enzymatic, autotrophic Fe(II) oxidation coupled to nitrate reduction forms poorly crystalline Fe(III) oxyhydroxides and proceeds without cellular encrustation while indirect Fe(II) oxidation via heterotrophic nitrate-reduction-derived nitrite can lead to green rust as an intermediate mineral and significant cell encrustation. The extent of encrustation caused by indirect Fe(II) oxidation by reactive nitrogen species depends on Fe(II) concentrations and is probably negligible under environmental conditions in most habitats.IMPORTANCE Most described nitrate-reducing Fe(II)-oxidizing bacteria (NRFeOB) are mixotrophic (their growth depends on organic cosubstrates) and can become encrusted in Fe(III) minerals. Encrustation is expected to be harmful and poses a threat to cells if it also occurs under environmentally relevant conditions. Nitrite produced during heterotrophic denitrification reacts with Fe(II) abiotically and is probably the reason for encrustation in mixotrophic NRFeOB. Little is known about cell-mineral associations in autotrophic NRFeOB such as the enrichment culture KS. Here, we show that no encrustation occurs in culture KS under autotrophic and mixotrophic conditions while heterotrophic nitrate-reducing isolates from culture KS become encrusted. These findings support the hypothesis that encrustation in mixotrophic cultures is caused by the abiotic reaction of Fe(II) with nitrite and provide evidence that Fe(II) oxidation in culture KS is enzymatic. Furthermore, we show that the extent of encrustation caused by indirect Fe(II) oxidation by reactive nitrogen species depends on Fe(II) concentrations and is probably negligible in most environmental habitats.

Stacking-Based Visualization of Trajectory Attribute Data.

Visualizing trajectory attribute data is challenging because it involves showing the trajectories in their spatio-temporal context as well as the attribute values associated with the individual points of trajectories. Previous work on trajectory visualization addresses selected aspects of this problem, but not all of them. We present a novel approach to visualizing trajectory attribute data. Our solution covers space, time, and attribute values. Based on an analysis of relevant visualization tasks, we designed the visualization solution around the principle of stacking trajectory bands. The core of our approach is a hybrid 2D/3D display. A 2D map serves as a reference for the spatial context, and the trajectories are visualized as stacked 3D trajectory bands along which attribute values are encoded by color. Time is integrated through appropriate ordering of bands and through a dynamic query mechanism that feeds temporally aggregated information to a circular time display. An additional 2D time graph shows temporal information in full detail by stacking 2D trajectory bands. Our solution is equipped with analytical and interactive mechanisms for selecting and ordering of trajectories, and adjusting the color mapping, as well as coordinated highlighting and dedicated 3D navigation. We demonstrate the usefulness of our novel visualization by three examples related to radiation surveillance, traffic analysis, and maritime navigation. User feedback obtained in a small experiment indicates that our hybrid 2D/3D solution can be operated quite well.

Interaction Support for Visual Comparison Inspired by Natural Behavior.

Visual comparison is an intrinsic part of interactive data exploration and analysis. The literature provides a large body of existing solutions that help users accomplish comparison tasks. These solutions are mostly of visual nature and custom-made for specific data. We ask the question if a more general support is possible by focusing on the interaction aspect of comparison tasks. As an answer to this question, we propose a novel interaction concept that is inspired by real-world behavior of people comparing information printed on paper. In line with real-world interaction, our approach supports users (1) in interactively specifying pieces of graphical information to be compared, (2) in flexibly arranging these pieces on the screen, and (3) in performing the actual comparison of side-by-side and overlapping arrangements of the graphical information. Complementary visual cues and add-ons further assist users in carrying out comparison tasks. Our concept and the integrated interaction techniques are generally applicable and can be coupled with different visualization techniques. We implemented an interactive prototype and conducted a qualitative user study to assess the concept's usefulness in the context of three different visualization techniques. The obtained feedback indicates that our interaction techniques mimic the natural behavior quite well, can be learned quickly, and are easy to apply to visual comparison tasks.